Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study

OBJECTIVES: We aim ed to evaluate a commercial artificial intelligence (AI) solution on a multicenter cohort of chest radiographs and to compare physicians' ability to detect and localize referable thoracic abnormalities with and without AI assistance. METHODS: In this retrospective diagnostic...

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Detalles Bibliográficos
Autores principales: Jin, Kwang Nam, Kim, Eun Young, Kim, Young Jae, Lee, Gi Pyo, Kim, Hyungjin, Oh, Sohee, Kim, Yong Suk, Han, Ju Hyuck, Cho, Young Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Chest
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9038825/
https://www.ncbi.nlm.nih.gov/pubmed/34973101
http://dx.doi.org/10.1007/s00330-021-08397-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9038825/
https://www.ncbi.nlm.nih.gov/pubmed/34973101
http://dx.doi.org/10.1007/s00330-021-08397-5

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